This invention relates to an improved system or apparatus for analysis of elevator traffic demand.
For more efficient operation of a plurality of elevator cars, the tendency is towards resorting to group control in which a most appropriate one of the elevator cars is occasionally selected as a function of changing traffic demand and in response to occurrence of a floor call.
However, it may frequently come to pass that the car most appropriate at the time of the floor call occurrence turns out to be inappropriate due to subsequent changes in traffic demand. Above all, with the instantaneous forecast system, i.e. a system in which a car corresponding to a floor call is indicated by an arrival forecast lamp upon actuation of the floor button, the result of occasionally poor selection is immediately apparent since car allocation, once made, cannot be changed easily.
On the other hand, transistion of traffic demand of a building over a one-day cycle occurs with a substantially fixed pattern.
In this consideration, it has been proposed to get the traffic demand encountered in the past during the same predetermined unit time periods recorded and processed statistically and to perform group control based on the traffic demand thus estimated for the time to come. In this manner, the efficiency of the group control operation may be improved drastically. In this case, the problem relating to the manner in which to process the past traffic volume data of the same unit time periods statistically and the manner in which to preestimate future traffic demand can be dealt with in broadly different ways.
In statistically processing the past traffic demand that occurred during the same predetermined unit time periods for preestimating the traffic demand for the time to come, it is not recommendable to study the data showing obviously different traffic demand from the usual value. For example, traffic demand may be markedly different on a particular day of the week, e.g. Sunday, or on any other day when an exceptionally large number of people visit the building. When the traffic demand data associated e.g. with Sunday are resorted to for traffic demand estimation in addition to the usual data, the resulting value is too small to be used for working days.